This study will demonstrate the application of prospective risk assessment to the outcome of acute care hospitalization (ACH) in the home health setting. Hospitalization is a key indicator of the effectiveness of home health care. It has significant implications for the patient and for resource utilization. Nationally, more than 25% of home health care episodes for Medicare beneficiaries result in a hospitalization. ACH is, however, an exceptionally complex outcome for home health care providers to manage effectively. Not all ACH are thought to be avoidable. Some hospitalizations may be unnecessary, and risks for avoidable hospitalization include transitions of care; communication and coordination of effort within home health agencies and between providers; patient and unpaid caregiver understanding of and adherence to care plans; managing distributed clinical processes in an uncontrolled environment; and monitoring patient progress. While there has been extensive epidemiologic study of patient risk factors, existing data sources and analytic methods provide only limited understanding of system and process risk sources. This study will use process analysis, subject matter expert input, fault tree analysis, and a systems-based review of 250 ACH events to develop a socio-technical probabilistic risk assessment (ST-PRA) model for ACH in the home [unreadable] health setting. This model will assist home health providers in isolating and managing sources of risk for avoidable ACH and provide a basis for transitions of care improvement efforts. The model development and case analysis process will be studied as a process that promotes sense making within home health agencies. This study will help home health providers to better understand important causes of preventable hospitalizations among their patients. Home health providers will be able to use this information to develop better care processes and to keep more people at home and out of the hospital. [unreadable] [unreadable] [unreadable]